Microbial communities present a huge diversity, which has been reported to exceed the abilities of current molecular methods (4). This elevated diversity makes difficult the analysis of microbial communities and, above all, their comparison through time series, spatial distribution, and other experimental treatments (16, 22).

Current analyses frequently involve the use of molecular fingerprinting methods as a relatively simple and rapid procedure to characterize each microbial community by a single profile (7, 10, 18, 19). At present, different fingerprinting methods are available, for example, denaturing gradient gel electrophoresis (DGGE) (18), terminal restriction fragment length polymorphism (15), and single-stranded conformational polymorphism (21), among others. Most of the pitfalls usually attributed to fingerprinting techniques are inherent to PCR amplification (26, 27), and the potential bias generated during the protocol equally affects cloning and sequencing, as well as any other PCR-based approaches (6, 14, 25), including new-generation sequencing methods (12). Fingerprinting techniques are especially useful for the comparison of microbial communities and the detection of community shifts induced by different treatments (5, 16).

Shifts in microbial communities represent highly sensitive indicators of changes in a given system, and this potential technology is of great interest in numerous scenarios (7). However, the large complexity of microbial communities often inhibits the detection of changes through fingerprinting analysis (1, 9). In this study, we propose a novel differential display (DD) fingerprinting method to discriminate DNA bands into different profiles. This discrimination is performed by the nucleotide following the 3′ end of the standard primers used in PCR amplification. DGGE is the fingerprinting technique used in this work, and the proposed DD-DGGE of microbial community fingerprints is aimed to facilitate the detection of differences between microbial communities. This technique is applied to a case study differentiating control and nitrate-supplemented wastewaters.

Materials and methods.

Two reactors continuously operating with primary effluent from the Guadalete wastewater treatment plant (Jerez de la Frontera, Cadiz, Spain) were used in this study as previously described (9). One of the reactors was supplemented with 0.24 mM (final concentration) calcium nitrate (Nutriox). Biofilms developed in the reactors were collected when a maximum difference between the sulfide concentrations in the control and supplemented reactors was observed (9). Collected samples were stored frozen at −80°C until processed. DNA was extracted, and 16S rRNA gene fragments were amplified by PCR following standard procedures described by Portillo et al. (23) but using the primers described below (Table 1) and the PCR thermal conditions proposed for primers Bac8F and Bac356R (13).

Microbial community fingerprints were carried out by DGGE (18) using a 6-h running time. Reverse primer Bac356R included a GC-rich tail sequence at its 5′ end for fragment stabilization during DGGE. Gels obtained by DGGE were digitized and analyzed as previously described (22) to estimate the quantitative ratios of selected bands in nitrate-supplemented versus control reactors.

Standard DGGE analyses resulted in molecular fingerprints with a high number of bands. In order to discriminate these bands into multiple molecular profiles, PCR amplifications were performed with primer pairs designed by the standard priming sequence plus a different nucleotide at the 3′ end. Thus, a total of 16 primer pairs (A-A, A-C, A-G, A-T, C-A, C-C, etc.) were prepared and the amplified products of these 16 reactions were run in separate lanes. Insilico evaluation of 16S rRNA gene sequences from RDP (Ribosomal Database Project) (3) showed that the sequences from different bacteria corresponded to distinct modified 3′-end primer pairs (Table 1), although a clear distribution of whole phyla within single primer pair combinations could not be established. Selected bands showing different intensities in the two treatments or absent from one of them were cut off the electrophoresis gels, reamplified, and sequenced (28). The sequences obtained were submitted for homology searches (2) at the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/Blast/).

Results and discussion.

DD techniques have long been applied in the clinic environment, preferentially focused on comparative analyses of gene expression (11, 20, 29). In this study, we applied a similar principle using selective 3′-end primer pairs for PCR amplification combined with a fingerprinting technique (DGGE), resulting in the DD-DGGE procedure, which greatly improves the ability to differentiate between bacterial communities and detect specific bacterial phylotypes when comparing complex microbial systems.

The discrimination of amplicons into different PCRs based on a differential 3′-end nucleotide of the amplification primers resulted in a distribution of the total bacterial community fingerprints into several subcommunities characterized by specific fingerprints. Some combinations of the forward and reverse primers used for DD-DGGE (Table 1) did not select any amplicon, and most of the members of the community were distributed into six combinations of modified 3′-end forward and reverse primers. This result is in agreement with an insilico evaluation of the proposed protocol which confirmed that some primer combinations rarely correspond to reported bacterial 16S rRNA gene sequences from RDP. Figure 1 shows the subcommunity fingerprints obtained from the successful combinations of primer pairs. Great similarity between the total-community fingerprints from the nitrate-supplemented and control reactors was observed, and no differences in the banding patterns were clearly visualized (Fig. 1T). This suggested that these communities presented scarce differences and that the DGGE procedure (i.e., PCR amplification, DGGE, and DD-DGGE) were highly reproducible. The subcommunity fingerprints (Fig. 1A to F) showed a distribution of the total number of bands in several profiles and even allowed the detection of additional bands corresponding to bacterial 16S rRNA genes remaining undetected in the total-community fingerprints. The subcommunity profiles showed less complexity that the global fingerprints, allowing the detection of several differences between the control and nitrate-supplemented reactors.

Molecular fingerprints of the total bacterial community (T) and partial communities (A to F) of samples from reactors with control (C) and nitrate-supplemented (N) wastewater. Partial community fingerprints correspond to those obtained by using different 3′-end primer sequences (Table 1) as follows: A, A (forward, Bac8Fa) and A (reverse, Bac356Ra); B, A (forward, Bac8Fa) and G (reverse, Bac356Rg); C, C (forward, Bac8Fc) and G (reverse, Bac356Rg); D, G (forward, Bac8Fg) and A (reverse, Bac356Ra); E, G (forward, Bac8Fg) and T (reverse, Bac356Rt); F, G (forward, Bac8Fg) and G (reverse, Bac356Rg); T, total community (forward, Bac8F; reverse, Bac356R). The operational taxonomic units identified are labeled as in Table 2.

Some of the clearest differences between the bacterial communities of our nitrate-supplemented and control reactors are indicated in Fig. 1 (labeled a to q). Table 2 shows the taxonomic affiliation of the bacteria corresponding to these selected bands. Besides, densitometric analysis of the DD-DGGE fingerprints allowed us to quantify the proportion that each selected band represented in the nitrate-supplemented and control reactors (Fig. 2). These bacteria showed enhancement or inhibition during nitrate addition. Bacteria belonging to the Alphaproteobacteria (Agrobacterium), Firmicutes (within the Clostridiales), Betaproteobacteria (Burkholderiales), and Actinobacteria (Streptomyces) were detected as being positively influenced by the addition of nitrate. However, some Alphaproteobacteria (Rhizobiales), Betaproteobacteria (Burkholderiales and Neisseriales), Firmicutes (different phylotypes within the Clostridiales), Acidobacteria, and Synergistetes were detected as being partially repressed by nitrate supplementation.

Quantitative analysis of the fluorescence intensities of the community fingerprints from the control (grey lines) and nitrate-supplemented (black lines) reactors compared in Fig. 1. The peaks corresponding to the operational taxonomic units identified are labeled as in Table 2.

Bands selected during DD-DGGE analysis and their taxonomic classificationsa

The bacteria identified during this study do not correspond to major nitrate-reducing, sulfide-oxidizing bacteria, as expected from a previous study (8). We have detected mainly heterotrophic bacteria generally reported in wastewaters but with scarce potential to decipher critical nutrient-cycling steps other that organic carbon decomposition. This result suggests that PCR amplification combined with DGGE analysis (DD-DGGE in this study) is able to detect only the most abundant components of bacterial communities (>1% of the total community) (17, 18). In a scenario dominated by heterotrophic bacteria, those representing a minor portion of the communities studied would only be occasionally detected using domain-wide primer pairs. The proportion of Sulfurimonas-like relatives detected using group-specific primers by García de Lomas et al. (8) constituted, at most, 0.1% of the total bacterial community. These results are in agreement with the high bacterial diversity reported in wastewaters (1, 9, 24) and indicate that DD-DGGE is a useful method to comparatively analyze the abundant members of bacterial communities from different treatments or sampling series. In the present work, the discrimination of bacterial phylotypes into different PCR amplifications and their display by DD-DGGE allowed us to simplify the DNA banding profiles and also improved the number of bands detected compared to the number detected by standard PCR and DGGE procedures.

Herein, a novel strategy for the comparative analysis of bacterial communities is proposed by combining 3′-end-discriminating primer pairs for PCR amplification and DGGE fingerprinting to obtain multiple subcommunities. The proposed procedure, DD-DGGE, provides a platform for the simple and rapid comparison of bacterial communities and the detection of their major components showing differential behavior between samples.

Nucleotide sequence accession numbers.

The nucleotide sequences determined in this study were deposited in GenBank under the accession numbers reported in Table 2.

ACKNOWLEDGMENTS

This work was supported mainly by grant P06-RNM-01787 from the Consejería de Innovación, Ciencia y Empresa, Junta de Andalucía, Spain, and by projects CGL2009-12328/BOS and Consolider CSD2009-00006 from the Spanish Ministry of Science and Innovation.

We acknowledge Aguas de Jerez E.M.S.A. for the use of the Guadalete wastewater treatment plant and for technical assistance and E. Iglesias from Yara Iberian for providing Nutriox.